# core/reasoning.py
"""
Reasoning System

Responsibilities:
- Coordinate reasoning components
- Integrate knowledge base queries
- Facilitate multi-step reasoning
- Generate reasoning chains
- Enforce reasoning constraints

Reasoning does NOT make autonomous decisions.
Reasoning does NOT bypass policy or domain boundaries.
Reasoning augments decision-making, does not replace it.
"""

from typing import List, Dict, Any, Optional
from dataclasses import dataclass
from enum import Enum


class ReasoningType(Enum):
    """
    Types of reasoning the system can perform.
    """
    DEDUCTIVE = "deductive"          # Logical inference
    INDUCTIVE = "inductive"          # Pattern recognition
    ABDUCTIVE = "abductive"          # Best explanation
    ANALOGICAL = "analogical"        # Similarity-based
    CAUSAL = "causal"                # Cause-effect


@dataclass
class ReasoningStep:
    """
    Single step in a reasoning chain.
    
    Fields:
    - step_id: Unique identifier
    - reasoning_type: Type of reasoning applied
    - input_facts: Facts used as input
    - inference: Inference made
    - confidence: Confidence score (0.0 - 1.0)
    - source: Knowledge source or rule used
    """
    step_id: str
    reasoning_type: ReasoningType
    input_facts: List[str]
    inference: str
    confidence: float
    source: Optional[str] = None


@dataclass
class ReasoningChain:
    """
    Complete chain of reasoning steps.
    
    Fields:
    - chain_id: Unique identifier
    - query: Original query
    - steps: Ordered list of reasoning steps
    - conclusion: Final conclusion
    - overall_confidence: Aggregated confidence
    - knowledge_sources: All sources used
    """
    chain_id: str
    query: str
    steps: List[ReasoningStep]
    conclusion: str
    overall_confidence: float
    knowledge_sources: List[str]


class ReasoningEngine:
    """
    Coordinates reasoning processes.
    
    Phase 1: Skeleton only
    Phase 2+: Implement reasoning logic
    Phase 2+: Integrate with knowledge base
    Phase 2+: Add model-assisted reasoning
    Phase 2+: Add reasoning validation
    """

    def __init__(self, knowledge_manager: Optional[Any] = None):
        """
        Initialize reasoning engine.
        
        Args:
        - knowledge_manager: Knowledge base manager (Phase 2+)
        """
        self.knowledge_manager = knowledge_manager
        self._chain_counter = 0

    def reason(
        self,
        query: str,
        context: Dict[str, Any],
        domain: str,
        max_steps: int = 10
    ) -> ReasoningChain:
        """
        Perform reasoning to answer a query.
        
        Phase 1: Stub (returns empty chain)
        Phase 2+: Implement reasoning logic
        
        Steps:
        1. Parse query into sub-questions
        2. Query knowledge base for relevant facts
        3. Apply reasoning rules
        4. Build inference chain
        5. Validate conclusions
        6. Assess confidence
        
        Args:
        - query: Question or problem to reason about
        - context: Additional context (identity, intent, etc.)
        - domain: Domain boundary for knowledge access
        - max_steps: Maximum reasoning steps
        
        Returns:
        - ReasoningChain with steps and conclusion
        """
        # TODO: Phase 2 - Parse query into sub-questions
        # TODO: Phase 2 - Query knowledge base
        # TODO: Phase 2 - Apply reasoning rules
        # TODO: Phase 2 - Build inference chain
        # TODO: Phase 2 - Validate against domain boundaries
        # TODO: Phase 2 - Assess overall confidence
        
        self._chain_counter += 1
        
        return ReasoningChain(
            chain_id=f"reasoning-{self._chain_counter}",
            query=query,
            steps=[],
            conclusion="NOT_IMPLEMENTED",
            overall_confidence=0.0,
            knowledge_sources=[]
        )

    def validate_reasoning(
        self,
        chain: ReasoningChain,
        domain: str
    ) -> bool:
        """
        Validate reasoning chain for correctness.
        
        Phase 2+: Check logical consistency
        Phase 2+: Verify knowledge sources are valid
        Phase 2+: Check domain boundaries not violated
        Phase 2+: Detect circular reasoning
        
        Returns:
        - True: Chain is valid
        - False: Chain has errors
        """
        # TODO: Phase 2 - Check logical consistency
        # TODO: Phase 2 - Verify all sources exist in knowledge base
        # TODO: Phase 2 - Check no cross-domain violations
        # TODO: Phase 2 - Detect circular reasoning
        # TODO: Phase 2 - Validate confidence calculations
        
        return True

    def explain_reasoning(self, chain: ReasoningChain) -> str:
        """
        Generate human-readable explanation of reasoning.
        
        Phase 2+: Format reasoning chain
        Phase 2+: Include confidence levels
        Phase 2+: Highlight key inferences
        Phase 2+: Note any uncertainties
        
        Returns:
        - Human-readable explanation string
        """
        # TODO: Phase 2 - Format chain as explanation
        # TODO: Phase 2 - Include confidence indicators
        # TODO: Phase 2 - Highlight critical steps
        # TODO: Phase 2 - Note limitations or uncertainties
        
        return "Reasoning explanation not implemented (Phase 1)"

    def query_knowledge(
        self,
        query: str,
        domain: str,
        max_results: int = 10
    ) -> List[Dict[str, Any]]:
        """
        Query knowledge base for relevant facts.
        
        Phase 2+: Query knowledge manager
        Phase 2+: Filter by domain
        Phase 2+: Rank by relevance
        Phase 2+: Return with confidence scores
        
        Returns:
        - List of knowledge facts with metadata
        """
        # TODO: Phase 2 - Query knowledge manager
        # TODO: Phase 2 - Apply domain filter
        # TODO: Phase 2 - Rank by relevance to query
        # TODO: Phase 2 - Include confidence scores
        
        return []

    def apply_rule(
        self,
        rule: str,
        facts: List[str],
        domain: str
    ) -> Optional[str]:
        """
        Apply reasoning rule to facts.
        
        Phase 2+: Load rule from rule base
        Phase 2+: Validate rule applies to domain
        Phase 2+: Execute rule logic
        Phase 2+: Return inference
        
        Returns:
        - Inferred fact, or None if rule doesn't apply
        """
        # TODO: Phase 2 - Load rule definition
        # TODO: Phase 2 - Validate rule domain
        # TODO: Phase 2 - Check preconditions
        # TODO: Phase 2 - Execute rule
        # TODO: Phase 2 - Return inference
        
        return None

    def assess_confidence(
        self,
        steps: List[ReasoningStep]
    ) -> float:
        """
        Assess overall confidence for reasoning chain.
        
        Phase 2+: Aggregate step confidences
        Phase 2+: Apply confidence decay for long chains
        Phase 2+: Consider source reliability
        
        Returns:
        - Overall confidence (0.0 - 1.0)
        """
        # TODO: Phase 2 - Aggregate step confidences
        # TODO: Phase 2 - Apply chain length penalty
        # TODO: Phase 2 - Weight by source reliability
        # TODO: Phase 2 - Return normalized confidence
        
        return 0.0

    def detect_contradictions(
        self,
        facts: List[str],
        domain: str
    ) -> List[tuple]:
        """
        Detect contradictions in fact set.
        
        Phase 2+: Compare facts for logical conflicts
        Phase 2+: Check against domain constraints
        Phase 2+: Report contradictory pairs
        
        Returns:
        - List of (fact1, fact2) contradictory pairs
        """
        # TODO: Phase 2 - Parse facts into logical form
        # TODO: Phase 2 - Check for direct contradictions
        # TODO: Phase 2 - Check for implied contradictions
        # TODO: Phase 2 - Validate against domain rules
        
        return []


class ReasoningError(Exception):
    """
    Exception raised when reasoning fails.
    
    Contains:
    - reason: Failure reason code
    - details: Human-readable details
    """
    def __init__(self, reason: str, details: str):
        self.reason = reason
        self.details = details
        super().__init__(f"{reason}: {details}")
